Preliminary assessment of fine-scale surface albedo based on 30-m Landsat or HJ series satellites over mountainous land surface

Abstract:

Satellite-based retrievals of land surface albedo are essential for surface energy budget. An increasing need of fine-scale albedo products is promoted in regional applications of radiative forcing and coarse scale albedo products validation. However, the long term fine-scale albedo products over mountainous areas are not available thus far. The largest barrier to retrieval fine-scale albedo products over mountainous areas was the lack of operational fine-scale multi-angular satellite observations, which considered the complex topographic effects, to derive land surface bidirectional reflectance distribution function (BRDF) models. Topography complicates the modeling and retrieval of land surface albedo due to shadow effects and the redistribution of incident radiation. What’s more, the topographic slope, aspect, and land cover types make the sloping surface more heterogeneous than the flat surface. Existing fine-scale albedo estimation algorithm require concurrent clear-sky surface reflectance observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) for providing the BRDF as a prior knowledge. However, it may sometimes be unavailable or carry uncertainties due to the complex topography. To overcome these problems, in this study we adopt the improved Angular Bin (AB) algorithm to estimate fine-scale satellite-based albedo over rugged terrain. The improved AB algorithm was developed base on the hypothesizes that the BRDF shape variations at fine spatial resolution is caused by the geometry of solar and sensor rather than the statistical parameters. An IGBP-based BRDF shape database was built firstly to retrieval sloping surface reflectance based on the Mountain-Radiation-Transfer (MRT) model. And then, a Look-Up-Table (LUT) among the surface reflectance and the broadband albedo was designed to directly estimate satellite-based fine-scale albedo by only applying one directional reflectance. The preliminary approach of the new built albedo estimation over mountainous areas was carried out in Heihe River Basin (BRB) by using the Chinese HJ series satellite. The validation results against ground measurements over various land cover types and topographic slopes show that our algorithm is effective for snow-free land surfaces and can achieve root-mean-square errors (RMSEs) of not more than 0.041. The larger discrepancy occurred in desert with an RMSE of 0.0409, which can be explain by the atmospheric correction during the process of sloping surface reflectance retrieval. The retrieved HJ albedo can improved the understanding of scale effects among different spatial resolution albedo products and can help to upscale in ground-based albedo measurements to coarse-scale during the multi-scale validation workflow.